1
Gaseous pollutants on rural and urban nursery schools in Northern Portugal
1
R.A.O. Nunes, P.T.B.S. Branco, M.C.M. Alvim-Ferraz, F.G. Martins, S.I.V. Sousa* 2
LEPABE – Laboratory for Process Engineering, Environment, Biotechnology and 3
Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, 4 Porto, Portugal 5 6 *Corresponding author: 7 Telephone: +351 22 508 2262 8 Fax: +351 22 508 1449 9
E-mail address: sofia.sousa@fe.up.pt 10
Postal address: Rua Dr. Roberto Frias, 4200-465, E215, Porto, Portugal 11
12 13
This article was published in Environmental Pollution, 208, 2-15, 2016 http://dx.doi.org/10.1016/j.envpol.2015.07.018
2
Abstract
14
Indoor air quality in nursery schools is different from other schools and this has been 15
largely ignored, particularly in rural areas. Urban and rural nursery schools have different 16
environmental characteristics whose knowledge needs improvement. Thus, this study 17
aimed to evaluate continuously the concentrations of CO2, CO, NO2, O3, CH2O and total
18
VOC in three rural nursery schools and one urban, being the only one comparing urban 19
and rural nurseries with continuous measurements, thus considering occupation and non-20
occupation periods. Regarding CO2, urban nursery recorded higher concentrations
(739-21
2328 mg m-3) than rural nurseries (653-1078 mg m-3). The influence of outdoor air was 22
the main source of CO, NO2 and O3 indoor concentrations. CO and NO2 concentrations
23
were higher in the urban nursery and O3 concentrations were higher in rural ones. CH2O
24
and TVOC concentrations seemed to be related to internal sources, such as furniture and 25
flooring finishing and cleaning products. 26
27
Capsule: Gaseous pollutant levels were higher in the urban nursery than in rural ones,
28
except for O3. High concentrations were due to lack of ventilation, outdoor air and internal
29 sources. 30 31 Keywords 32
Indoor air, nursery, children, rural, urban, gaseous 33
3
1. Introduction
35
In recent years, numerous scientific studies highlighted that citizens spend most of their 36
time in indoor environments (Jenkins et al., 1992; Silvers et al., 1994; Klepeis et al., 2001; 37
Schweizer et al., 2007; de Gennaro et al., 2014; Wu et al., 2015). The largest part of 38
human exposure to air pollution occurs in indoor environments, commonly considered 39
non-polluted such as homes, offices and schools (WHO 2006; de Gennaro et al., 2014; 40
Branco et al., 2014). Nevertheless, it is actually known that indoor air pollution has equal 41
or even greater impact on human health than outdoor pollution.This occurs because time 42
spent indoor is usually higher than time spent outdoor; also, there is a great variety of 43
indoor sources, that include outdoor and specific indoor sources associated with 44
formaldehyde and volatile organic compounds (VOC) emissions, leading frequently to 45
higher concentration than outdoor (Franklin 2007; Faustman et al. 2000; Sofuoglu et al. 46
2011). Furthermore, children are more vulnerable to air pollution exposure than adults, 47
being considered a risk group (Sousa et al., 2012). Exposure to indoor air pollution has 48
been related to long and short-term health problems. Respiratory, cardiovascular and 49
central nervous systems are the most affected, leading also to adverse effects on children's 50
productivity and academic performance (Jones 1999; Wang et al., 2015; Annesi-Maesano 51
et al., 2013, Mohai et al., 2011). 52
Indoor pollutant sources are related to structural conditions of buildings (interior finishes, 53
coverings and furniture), occupants’ activities (heating, cooling and cooking habits, 54
metabolism, hygiene, cleaning and disinfection products) and outdoor pollution (Jones, 55
1999). The control and analysis of indoor air quality (IAQ) assume an extremely 56
important role because indoor pollutants’ concentrations may vary significantly with 57
location and time (de Gennaro et al., 2014). Studies of IAQ in schools have been 58
performed mainly in primary or secondary schools. Nevertheless, IAQ in nursery schools 59
4 is different from other schools and this has been largely ignored, particularly in rural areas 60
(Ashmore and Dimitroulopoulu, 2009). IAQ studies comparing urban and rural contexts 61
are relevant because there are evident environmental and social differences. On the 62
environmental level this idea is supported essentially by the influence of traffic emissions. 63
On the social level, habits and life styles in these two contexts are significantly different. 64
Studies already made in nursery schools were essentially of three types: i) only focusing 65
on comfort parameters (Gladyszewska-Fiedoruk 2013), and/or on CO2 concentration as
66
global IAQ indicator (Theodosiou and Ordoumpozanis, 2008; Carreiro-Martins, 2014); 67
or ii) focusing on the study of one specific pollutant such as PM, allergens or phthalates 68
(Arbes, et al., 2005; Fromme, et al., 2013). As far as known there are only five studies 69
focussing on various gaseous pollutants in nursery schools' indoor air, from which one 70
was in rural areas. Zuraimi and Tham (2008) investigated comfort parameters, air velocity 71
and air exchange rates, as well as concentrations of several pollutants in nursery schools 72
of Singapore, concluding that outdoor concentrations and occupant density were the main 73
determinants for CO2 concentrations. For indoor CO and O3 levels, outdoor
74
concentrations were the main precursors. Yang et al. (2008) characterized the 75
concentrations of different indoor air pollutants in Korean nursery schools and compared 76
them according to age and characteristics of buildings. The main problems reported in 77
that study were caused by chemicals emitted from building materials or furnishing, and 78
insufficient ventilation rates. Yoon et al. (2011) measured IAQ in rural and urban 79
preschools in Korea, by investigating the indoor air concentrations of PM and several 80
chemical compounds, and they found evidences that pollutant concentrations were in 81
general higher in urban context and indoors than in rural context and outdoors. However, 82
indoor/outdoor (I/O) ratios of CH2O, CO and total volatile organic compounds (TVOC)
83
were higher in rural schools. 84
5 Cano et al. (2012) studied IAQ in nursery schools in Lisbon and Porto (Portugal) 85
considering various chemical pollutants, comfort parameters and microbiological 86
parameters. The results of that study demonstrated an association between CO2
87
concentrations and the number of children present in classrooms, as well as the need to 88
improve ventilation and comfort of the spaces to promote healthier indoor environments. 89
Despite considering a large number of nursery schools, gaseous compounds, comfort 90
parameters and comparisons between rural and urban nursery schools, in the above 91
mentioned studies, samplings were only conducted during weekdays and during 92
occupation periods. That did not allow understanding differences in IAQ between 93
occupation and non-occupation periods (including nights and weekends), which permit 94
to better understand sources of indoor air pollution, as well as the baseline room scenario. 95
Additionally, some chemical compounds were measured by passive sampling and not 96
continuously. Moreover, some important compounds were missing as for example NO2,
97
which is an important traffic marker. 98
Following Nunes et al. (2015) study that focused on the PM assessment, and in the scope 99
of INAIRCHILD project (Sousa et al., 2012), the present study is the only one comparing 100
urban and rural nurseries with continuous measurements considering the comparison of 101
occupation and non-occupation periods, thus aiming to reduce the above referred gaps. 102
Therefore, the continuous evaluation of the indoor concentrations of CO2, CO, ozone
103
(O3), NO2, TVOC and formaldehyde (CH2O) on different indoor microenvironments,
104
namely classrooms and lunch rooms was performed. Furthermore, gaseous 105
concentrations were compared with Portuguese legislation and WHO guidelines for IAQ 106
and children’s health. 107
6
2. Materials and methods
109
IAQ measurements were made in three different rural nursery schools (RUR1, RUR2 and 110
RUR3) located in Bragança district and without significant influence of traffic emissions 111
and in one urban nursery (URB) located in Porto and influenced by traffic emissions. 112
Table 1 shows a general description of each studied microenvironment of RUR1, RUR2, 113
RUR3 and URB, namely regarding the type of use, children’s age, building floor, area, 114
number of occupants, period of occupation, ventilation routines and sampling time. 115
Measurements were performed in two classrooms in RUR1 and RUR3, one classroom in 116
RUR2, and three classrooms in URB, as well as in the lunch rooms of all nursery schools. 117
Indoor air gaseous compounds, namely CO2, CO, NO2, O3, CH2O and TVOC, were
118
continuously measured (at least 24 h in each ME) using an Haz-Scanner IEMS Indoor 119
Environmental Monitoring Station (SKC Inc., USA), equipped with high sensitive 120
sensors using the following methods: i) CO2 – nondispersive infrared (NDIR) detection;
121
ii) CO, O3, NO2 and CH2O – electrochemical detection; iii) VOC – photoionization
122
detection (PID). All concentrations were converted from ppb and ppm (units from data 123
log), to ease the comparisons with legislation and guidelines using conversion factors 124
(Nota Técnica NT-SCE-02 2009; Tiwary and Colls, 2010). These conversion factors are 125
normalized to 293 K and 101.3 kPa, therefore concentrations were corrected for 126
temperature, using the values measured, and admitting an atmospheric pressure of 1 atm. 127
The equipment was submitted to a standard zero calibration (available in the equipment) 128
and data were validated prior to each new measurement (in each new room). Indoor 129
measurements were performed in each room studied, and, in some cases, both on 130
weekdays and weekends, between April and June 2014. Measurements were recorded 131
each minute and hourly means were calculated. In RUR1 measurements were made in 132
7 full occupation and partial occupation for one of the classrooms and in the lunch room. 133
Full occupation concerned the usual period of nursery attendance and partial occupation 134
concerned to one week before the period of the Easter holidays, where the classroom’s 135
occupation was reduced. 136
The indoor hourly mean values were compared with reference standards and guidelines 137
for general indoor environments, aiming to evaluate exceedances. Comparisons were 138
performed considering national and international reference values for general indoor 139
environments, namely: i) Portuguese legislation (8 hour means) (Portaria nº353-A/2013) 140
for CO2 (2250 mg m-3, plus 30% of margin of tolerance (MT) if no mechanical ventilation
141
system was working in the room), CO (10 000 µg m-3), CH2O (100 µg m-3), and TVOC
142
(600 µg m-3, plus 100% of MT if no mechanical ventilation system was working in the
143
room); ii) WHO guidelines (WHO, 2010) for CO (35000 µg m-3 for hourly mean), NO2
144
(200 µg m-3 for hourly mean) and CH2O (100 µg m-3 for 30 minutes mean). For the
145
Portuguese legislation, 8-hour running means for all pollutants were calculated and the 146
daily maximum was compared to the standard. 147
Hourly O3 and NO2 outdoor concentrations were obtained to calculate I/O ratios for rural
148
nursery schoolsin the subsequent days after indoor measurements and with the same 149
equipment used indoors; for the urban nursery outdoor concentrations were monitored at 150
the nearest air quality station from the Air Quality Monitoring Network of the Porto 151
Metropolitan Area, managed by the Regional Commission of Coordination and 152
Development of Northern Portugal (Comissão de Coordenação e Desenvolvimento 153
Regional do Norte) under the responsibility of the Ministry of Environment. This station
154
is classified as urban traffic and is representative of the urban area studied. 155
8 Mean, minimum, maximum, median and standard deviation (SD) values were calculated 156
for the hourly mean data of indoor air pollutants’ concentrations in occupation and non-157
occupation periods and weekend periods. Data was tested for normality using both the 158
Shapiro-Wilk and Anderson-Darling tests. Whenever measurements were performed for 159
more than one day differences between mean hourly concentrations measured in different 160
sampling days were tested using t-test for normal distributions and Mann–Whitney’s U 161
test for the other distributions. Differences between weekdays and weekends as well as 162
between rural and urban context were also studied using t-test for normal distributions 163
and Mann–Whitney U test for the other distributions. For all analyses a significance level 164
of 0.05 was considered. Descriptive statistics for the parameters were calculated using 165
MS Excel® (Microsoft Corporation, USA), and other statistical analyses were computed
166
using R software, version 3.1.2 (R Foundation for Statistical Computing, 2014). 167
3. Results and Discussion
168
Tables 2, 3 and 4 summarize the main statistical parameters (minimum, maximum, mean, 169
median and standard deviation) of the hourly mean data for each room considering the 170
entire sampling period for weekdays occupation periods, weekdays non-occupation 171
periods and weekends, respectively. Mean daily profiles were performed to represent 172
mean IAQ scenarios for weekdays and weekends. When comparing two or more 173
consecutive sampling days (weekdays and weekends), statistical differences regarding 174
CO2 (p > 0.05 in all cases) were not found; however, for CO, NO2, O3, CH2O and TVOC
175
statistical differences (p < 0.05) were found in 50, 75, 50, 25 and 50% of the cases, 176
respectively. Nevertheless, similarly to what was performed by Branco et al. (2015), a 177
daily mean scenario was assumed for all pollutants allowing the following analyses. 178
3.1 Average daily profiles
9
3.1.1 Ventilation indicator - CO2
180
Average daily profiles of CO2 for all the studied nursery schools are represented in Figure
181
1: a) RUR1, b) RUR2, c) RUR3 and d) URB. 182
Two peaks of CO2 concentrations were observed in the classrooms: i) during morning -
183
rising in early morning and decreasing before lunch time; and ii) during afternoon - rising 184
after lunch time and decreasing until the end of the afternoon. In lunch rooms, three peaks 185
were observed corresponding to the breakfast, lunch and snack times in RUR1 and RUR2, 186
and two peaks corresponding to the lunch and snack times in the remaining nursery 187
schools. Consequently, all these peaks were found during occupation periods. 188
A large difference was found between daily profiles on weekdays and weekends. For the 189
latter, concentrations were usually found bellow 1000 mg m-3 in all studied nursery
190
schools. During meals lower concentrations were observed in the classrooms, although 191
never lower than in non-occupation periods (night, dawn and weekends). 192
Exceptions for the general profiles above described were found for: i) classroom B of 193
RUR3, characterized by a small increase during the occupation period, which might have 194
been due to the usage of this room as a support room, namely for material storage and for 195
only one baby sleeping period, thus having low occupation for a short period; ii) 196
classroom B of URB, characterized by a continuous increase of CO2 concentrations
197
throughout the day from early morning until late afternoon. This was probably due to the 198
lack of ventilation (closed windows) during the morning and sleeping period (12h to 15h), 199
leading to the highest concentrations (7448 mg m-3). Before the sleeping period the
200
windows were opened and CO2 concentrations started to decrease until the early evening
201
when they stabilized close to the minimum value (708 mg m-3).
10 Windows and doors closed during classrooms’ occupation periods (to avoid noise and 203
reducing/increasing indoor temperatures) also caused the highest CO2 concentrations
204
found by Yang et al. (2009) (5813 mg m-3) and by Yoon et al. (2011) (3088 mg m-3) for 205
urban nursery schools, although lower than those reported for classrooms B and C of 206
URB. The same was verified by Branco et al. (2015) for urban nursery schools. 207
Gładyszewska-Fiedoruk (2011) reported similar CO2 concentrations in a nursery school
208
at north-eastern Poland, and also highlighted the importance of good natural ventilation. 209
Classroom C of URB that had natural ventilation, recorded on average, for occupation 210
periods, higher concentrations (mean ± SD: 2087±971 mg m-3) than the rooms of rural 211
nursery schools also naturally ventilated, which might have been due to the occupational 212
densities. This is in fact another determining factor for the indoor air concentrations of 213
CO2 in classrooms. Therefore, it was possible to observe that classroom C of URB had
214
higher occupation density than the above referred rural classrooms. In general, the 215
occupational densities were found higher in the urban nursery school than in the rural 216
ones (Table 1). 217
Global concentrations found in rural nursery schools were on average lower than those in 218
the urban nursery school during occupation periods (mean ± SD: 1408 ± 388 mg m-3 and 219
2273 ± 943 mg m-3, respectively), non-occupation periods (mean ± SD: 795 ± 97 mg m-3 220
and 976 ± 83 mg m-3, respectively) and weekends (mean ± SD: 676 ± 14 mg m-3 and 799 221
± 60 mg m-3, respectively). Yoon et al. (2011) reached the same conclusion in their study, 222
reporting higher concentrations of CO2 in urban pre-schools (1525 mg m-3) than in rural
223
ones (995 mg m-3). Theodosiou and Ordoumpozanis (2008) that studied the thermal 224
environment and IAQ in kindergartens and primary schools in Kozani (Greece) and 225
Carreiro-Martins (2014) that evaluated the association between reported wheezing and 226
measured indoor CO2 and other environmental comfort parameters in day care centres of
11 Porto and Lisbon, reported higher mean concentrations (2700 mg m-3 and 2592 mg m-3,
228
respectively) than those recorded in all nursery schools in this study. Cano et al. (2012) 229
reported for urban pre-schools of Porto a higher mean concentration (3145 mg m-3) than 230
that registered in URB (mean ± SD: 2273 ± 943 mg m-3 for occupation periods). Zuraimi 231
and Tham (2008) reported for nursery schools in Singapore concentrations similar to 232
those found in classrooms A and B of URB. Yoon et al. (2011) reported for rural nursery 233
schools similar concentrations to those found in classrooms A of RUR1 (full occupation) 234
and RUR2 and in classroom B of RUR3. 235
3.1.2 Traffic related pollutants - CO, NO2 and O3
236
Figures 2, 3 and 4 show CO, NO2 and O3 hourly mean concentrations in: a) RUR1, b)
237
RUR2, c) RUR3 and d) URB. For O3, daily distributions of hourly mean concentrations
238
were only represented for a) RUR1 – Classroom A in full occupation (week), Classroom 239
A in partial occupation, Classroom B (week and weekend) and lunch room in full 240
occupation and partial occupation; b) RUR2 – Classroom A (week) and lunch room; c) 241
RUR3 – Classroom A (week) and d) URB. The remaining profiles were not represented 242
because O3 concentrations were below or very close to the minimum detection limit of
243
the equipment (1 ppb). 244
Regarding CO concentrations, it was possible to distinguish a similar daily profile in all 245
the studied buildings, especially on weekdays, when concentrations increased early in the 246
morning until the end of the afternoon, matching with anthropogenic activities mainly 247
related with work/school-to-home-to-work/school routes, thus showing the probable 248
outdoor influence. During night and early morning concentrations tended to decrease. 249
For NO2 concentrations, statistically different average daily profiles were found for all
250
nursery schools (p < 0.05). Oscillations might have been related with ventilation (door 251
12 and /or windows opening), reducing NO2 concentrations, and with accumulation (in
252
RUR2 for example), increasing NO2 concentrations. In RUR3, slight increases were only
253
verified in occupation periods; however, concentrations were on average significantly 254
higher (p < 0.05) than in RUR1 and RUR2. In URB, NO2 daily profiles corresponded to
255
the daily traffic patterns, where there were increases in the morning and late afternoon. 256
The major cause for the increase of indoor NO2 concentrations was the exhaust gases’
257
emission from outdoors, which was very clear in classroom A of RUR3, with windows 258
facing the parking area, recording 291.66 µg m-3 at 18h (time of parents’ arrival). 259
Nevertheless, in some cases the accumulation of this pollutant and lack of rooms’ 260
ventilation were the factors that contributed the most to the concentrations recorded (as 261
in classroom B in RUR1). 262
CO and NO2 concentrations obtained in URB for occupation, non-occupation and
263
weekend periods were on average higher (CO - 3608.7 ± 1175.1 µg m-3, 3053.0 ± 1024.0 264
µg m-3 and 3218.4 ± 669.5 µg m-3, respectively; NO2 – 63.87 ± 43.21 µg m-3, 62.99 ±
265
45.40 µg m-3 and 104.80 ± 47.61 µg m-3, respectively) than those registered in rural 266
nursery schools (CO – 3109.3 ± 830.5 µg m-3, 2817.5 ± 863.9 µg m-3 and 2439.8 ± 195.6
267
µg m-3, respectively; NO2 – 47.13 ± 43.04 µg m-3, 44.96 ± 41.59 µg m-3 and 61.51 ± 39.95
268
µg m-3), which can be explained by the influence of road traffic from outdoor air, as no 269
indoor sources were present. Yang et al. (2009) and Wichmann et al. (2010) also pointed 270
to road traffic as responsible for high concentrations of CO and NO2 in South Korean
271
urban pre-schools and in Sweden homes, pre-schools and schools, respectively. In the 272
lunch rooms, CO and NO2 concentrations were on average lower than those recorded in
273
the classrooms, except for RUR1, probably due to emissions from gas stoves in the lunch 274
room of this school. 275
13 Regarding weekend periods, CO and NO2 daily profiles seemed almost constants
276
throughout the day, however, CO concentrations in URB showed a similar profile to that 277
recorded for weekdays. Despite this, in all nursery schools concentrations on weekends 278
were significantly lower (p < 0.05 in all cases) than those recorded on weekdays, once 279
the nursery schools were closed being the influence from outdoors restricted. For NO2,
280
all nursery schools showed profiles with the same order of magnitude as those recorded 281
on weekdays. CO concentrations obtained in the four nursery schools studied, both for 282
weekdays and weekends, were substantially higher than those reported by Yoon et al. 283
(2011) (1512.0 µg m-3). Cano et al. (2012) reported much lower concentrations in Porto 284
pre-schools (478 µg m-3) than those recorded in the nursery schools here studied; 285
however, for Lisbon pre-schools the reported concentrations (3888 µg m-3) were similar
286
to some of those here recorded (classrooms A of RUR2 and RUR3 and in classrooms A 287
and C of URB). Wichmann et al. (2010) reported for kindergartens in Stockholm, 288
Sweden, similar NO2 concentrations (12.4 µg m-3) to some of those here stated (classroom
289
A in full occupation and in the lunch rooms in full occupation of RUR1, and RUR2 and 290
RUR3). 291
Regarding O3, concentrations were higher during the afternoons in all nursery schools.
292
The maxima concentrations were recorded between 16h and 19h related with cleaning 293
activities and windows opening. The peak observed in RUR3 was similar to that recorded 294
for NO2, and the outdoor air appeared to be the main cause for the O3 indoor air
295
concentrations. In RUR2 and URB, the maximum concentrations were recorded in lunch 296
rooms during clean-up activities, which were frequently associated with windows 297
opening and consequent influence of outdoor air. Rural nursery schools recorded 298
significantly higher (p < 0.05) concentrations than URB. In the inexistence of indoor 299
sources, which happened in all nursery schools of this study, outdoor air is expected to 300
14 have been the main determinant of indoor O3 concentrations, as already identified in
301
several studies (Sousa et al., 2009; Bayer-Oglesby et al., 2004; Duenas et al., 2004; Syri 302
et al., 2001). O3 outdoor concentrations are clearly higher in rural areas than urban ones,
303
thus reproducing the same behaviour indoors. Generally, O3 concentrations were lower
304
on weekends than on weekdays, being zero in most cases, which reinforces the influence 305
of outdoor air. 306
Zuraimi and Tham (2008) reported higher O3 concentrations (59 µg m-3) than those in the
307
nursery schools of this study, probably due to cleaning routines and outdoor air 308
contributions. 309
In general, the influence of outdoor air could be associated with the observed indoor 310
concentrations of CO, NO2 and O3, which could be supported by the inexistence of indoor
311
sources (in majority of cases) as well as by the I/O ratios results (presented in Section 312
3.4). 313
3.1.3 TVOC and CH2O
314
Figure 5 shows TVOC hourly mean concentrations determined for all the studied class 315
and lunch rooms of the four nursery schools: a) RUR1, b) RUR2, c) RUR3, and d) URB). 316
RUR1 and RUR2 showed a nearly constant profile throughout the day; in RUR3 maxima 317
concentrations were found during dawn and in URB occurred mainly during occupation 318
periods. In lunch rooms, the highest concentrations were recorded immediately after 319
lunch and snack times. Although it was not possible to find a typical profile for TVOC 320
concentrations in the studied nursery schools, all recorded peaks seemed to be related 321
with: i) the cleaning activities (products emitting VOC), which were performed mostly in 322
the late afternoon in the classroom and after lunch in the lunchrooms; ii) with the 323
accumulation phenomenon caused by the lack of ventilation after these activities; for 324
15 partial occupation period in RUR1, a deeper cleaning was performed, thus higher 325
concentrations of TVOC were recorded in the lunch room as well as in classroom A; and 326
iii) in URB, the frequent peaks during occupation periods seemed to be related with 327
insufficient ventilation, boosting accumulation during sleeping time (12h to 15h). After 328
sleeping time concentrations decreased, as the room was ventilated. 329
The concentrations recorded on weekends, when above the detection limit, seemed to be 330
constant and almost the same as those recorded for non-occupation periods (night and 331
dawn) during the week, except for RUR3. In this nursery school there were probably 332
specific indoor sources of those pollutants, namely building materials such as wood 333
clusters, plywood and furniture materials, because besides increasing during weekends 334
(classroom A), a progressive increasing from the end of the day until the following 335
morning on weekdays was observed in classrooms A and B. Classroom A of RUR2 and 336
Classroom C of URB reported concentrations for occupation periods (mean ± SD: 117.66 337
± 17.59 µg m-3 and mean ± SD: 124.58 ± 89.62 µg m-3, respectively), similar to those 338
reported by Yang et al. (2009) (123.00 µg m-3). Classroom B of RUR1 reported 339
concentrations for occupation periods (mean ± SD: 155.22 ± 115.11 µg m-3) similar to
340
those reported by Cano et al. (2012) (181.00 µg m-3). Roda et al. (2011) that investigated 341
IAQ in Paris child day care centers and St-Jean et al. (2012) that studied IAQ in Montréal 342
reported lower TVOC concentrations than those reported for nursery schools in this study 343
(12.75 µg m-3 and 22.90 µg m-3, respectively). In these two studies, the authors concluded 344
that indoor TVOC concentrations were caused by emissions from building materials and 345
furniture, worsened by insufficient ventilation rates. 346
TVOC mean concentrations recorded for occupation periods in rural nursery schools were 347
lower (mean ± SD: 145.18 ± 128.15 µg m-3) than those reported by Yoon et al. (2011) 348
(351.00 µg m-3) and similar to those reported by Yang et al. (2009) (162.69 µg m-3). 349
16 However, both these studies concluded that those concentrations were caused by 350
emissions from building materials and furnishing. Cano et al. (2012) reported in Lisbon 351
much higher concentrations (3339.00 µg m-3) than those found in this study. In general, 352
for occupation periods the urban nursery recorded higher mean TVOC concentrations 353
(mean ± SD: 271.66 ± 216.42 µg m-3) than rural ones (mean ± SD: 145.18 ± 128.15 µg 354
m-3), and Yoon et al. (2011) found the same for the South Korean nursery schools.
355
Figure 6 shows CH2O hourly mean concentrations for: a) classroom A (weekend),
356
classroom B (weekdays) and the lunch room in full occupation of RUR1; b) the lunch 357
room of RUR2; c) the lunch room of RUR3; and d) URB. CH2O concentrations for the
358
remaining studied rooms are not represented because they were below the minimum 359
detection limit of the equipment (0.05 ppm). 360
For CH2O concentrations a daily pattern was found in URB. In this nursery school it was
361
possible to identify three concentration peaks in classrooms A and B and in the lunch 362
room, recorded on weekdays. In classroom A the peak was between 11h and 13h, 363
corresponding to the lunch and cleaning time as well as to the preparation for the sleeping 364
period (children were less than 2 years old and spent the entire school day inside the 365
classroom). CH2O concentrations’ increase might have been related with the products
366
used for cleaning. Furthermore, certain activities such as dragging wood furniture 367
(scraping the floor) to prepare the classroom for sleeping time could be connected with 368
the emission of this pollutant. The other two peaks corresponded to the cleaning periods 369
in the lunch room (before lunch) and cleaning before sleeping time and children’s hygiene 370
in classroom B. Besides the recorded peaks, concentrations increased at the end of the 371
day, in agreement with the period of general cleaning of the entire building. After that, 372
the building was closed and the concentrations of CH2O increased due to the
373
accumulation at the end of the night, and gradually decreased throughout the morning. In 374
17 RUR1 (full occupation), RUR2 and RUR3 two concentrations peaks were recorded in the 375
lunch rooms at lunch time probably related with furniture dragging (furniture finishing - 376
varnished wood). On average, URB registered higher CH2O concentrations for
377
occupation and non-occupation periods (44.19 ± 42.99 µg m-3 and 60.63 ± 60.83 µg m-3, 378
respectively) than those registered in rural nursery schools (18.42 ± 34.03 µg m-3 and 1.54 379
± 2.77 µg m-3, respectively) and lower for weekend periods (1.33 ± 1.15 µg m-3 and 3.68
380
± 6.37 µg m-3, respectively). CH2O mean concentrations recorded for occupation periods
381
in URB were much higher than those reported by the European Commission in AIRMEX 382
project (European Indoor Air Monitoring and Exposure Assessment) (2003-2008) for 383
schools and kindergartens (the maximum mean value recorded was 31.9 µg m-3 in Leipzig 384
during July). For Athens, Budapest and Helsinki schools and kindergartens, (20.2 µg m
-385
3, 18.23 µg m-3 and 21.23 µg m-3, respectively) (Kotzias et al., 2009) as well as in the
386
kindergartens analysed in the SINPHONIE project (Schools Indoor Pollution and Health: 387
Observatory Network in Europe) (15 ± 10 µg m-3) (Jantunen et al., 2008), concentrations 388
were similar to those recorded in occupation periods of rural nursery schools. 389
Furthermore, CH2O mean concentrations in schools of Nijmegen, Catania, Thessaloniki
390
and Nicosia (6.1 µg m-3, 13.0 µg m-3, 13.8 µg m-3, 12.0 µg m-3, respectively), also reported 391
in AIRMEX project, were lower than those reported in this study (Kotzias et al., 2009). 392
Concluding, TVOC higher concentrations in RUR1, RUR2 and URB were mainly caused 393
by cleaning activities (products used). In RUR3 internal sources, namely building 394
materials and furniture finishing, were the probable causes for the concentrations 395
recorded. The lack of ventilation increased even more significantly the concentrations 396
recorded. Regarding CH2O, dragging of furniture in RUR1, RUR2 and RUR3 lunch
397
rooms during meal time appeared to have been the main responsible for the CH2O
18 concentrations recorded. In URB, concentrations seemed to have been related with 399
cleaning activities and poor ventilation. 400
A careful choice of materials which do not emit VOC must be prioritized to improve IAQ 401
and to protect children’s health. Furthermore, improved ventilation rates will allow the 402
reduction of indoor concentrations of these pollutants. 403
3.3 Comparison with standards and guidelines
404
Table 5 shows the number of non-compliances and exceedances (%) to the standards and 405
guidelines referred to in the Material and methods section. 406
WHO guidelines for CO, NO2 and O3 concerning 1h, 8h and 24h means were never
407
exceeded. However, WHO guideline for 30 minutes CH2O mean was always exceeded
408
during occupation periods in the lunch rooms of RUR1, RUR2 and RUR3, probably due 409
to furniture dragging (tables and chairs) during meal times. In URB, exceedances were 410
around 28% in all the studied rooms during occupation periods, being lower than in rural 411
nursery schools. Classrooms A and B also recorded CH2O exceedances for the Portuguese
412
legislation (100% in both classrooms). These values were probably due to emissions from 413
cleaning products, furniture and flooring which were varnished wood. Missia et al. (2010) 414
reported CH2O concentrations (5.8-62.6 µg m-3) below the WHO guideline. CH2O
415
concentrations reported in AIRMEX and SINPHONIE projects could not be compared 416
with the WHO guideline (30 minutes), because measurements were one week long. 417
Exposure to CH2O concentrations may cause inflammation of the airways and adverse
418
pulmonary effects (Venn et al., 2003, Jones, 1999). To minimize the concentrations 419
recorded, higher ventilation in the rooms with the highest concentrations should be 420
implemented, and materials free from CH2O emissions should be preferred whenever
421
possible. 422
19 According to Portuguese legislation for CO2, exceedances were recorded in classrooms
423
A and B of URB (50% and 100%, respectively). Classrooms A of RUR3 and C of URB 424
had natural ventilation so the margin of tolerance was applied, thus no exceedances were 425
observed. A determining factor for the indoor air concentrations of CO2 that is not taken
426
into account by the Portuguese legislation is the occupation density of the classrooms. In 427
fact, Portuguese legislation regarding the number of children per classroom for infants 428
under 3 years old (Portaria nº 262/2011) and for pre-schoolers (Despacho nº 5048-429
B/2013) which only considers educational and economic criteria, legislate for infants, 430
groups aged 1 to 2 year old (until the acquisition of march) and groups aged 2 to 3 years 431
old, a maximum of, respectively, 10, 14 and 18 children per group. For pre-schoolers a 432
minimum of 20 and a maximum of 25 children per classroom is legislated. Beyond that, 433
there is a guideline recommended by ASHRAE for classrooms (for children between 5 434
and 8 years old) that considers the density of occupation (25 occupants per 100 m2) 435
(ASHRAE, 2007). Although only classroom C of URB has exceeded the value of the 436
Portuguese legislation regarding the number of children per classroom for pre-schoolers 437
(Despacho nº 5048-B/2013), all classrooms of this study exceeded ASHRAE 438
recommended guideline. Branco et al. (2015) also found exceedances to ASHRAE 439
recommended guideline for all urban nursery schools analysed. This circumstance as well 440
as ventilation habits referred in Section 3.1, led to the increase of CO2 concentrations in
441
classrooms to values above the Portuguese legislated standards. Theodosiou and 442
Ordoumpozanis (2008) and Zuraimi and Tham (2008) also pointed out the higher 443
occupation densities as an important factor for the increase of indoor CO2 concentrations.
444
St-Jean et al. (2012) also referred a high occupational density when comparing with 445
ASHRAE recommendation and indicated high occupation density as an important factor 446
for the increase of CO2 concentrations.
20 Headache, nausea, breathlessness and loss of concentration are possible health symptoms 448
for children attending these nursery schools (USEPA 2009; Griffiths and Eftekhari, 449
2008). 450
For TVOC, exceedances were recorded in classroom A of RUR3 (33%) and in classrooms 451
A and B of URB (50% and 100%, respectively). According to the analysis previously 452
performed, these exceedances may have been caused by specific point activities 453
performed in the classrooms (A and B of URB), associated with the use of paints and 454
glues, as well as by the probable existence of internal sources of these pollutants such as 455
furniture materials, finishing (paints and varnishes), decoration and construction products 456
(classroom A of RUR3). Missia et al. (2010) and Zhang and Niu (2003) also associated 457
finishing products, coatings and building materials (carpets, acoustic and thermal 458
insulation) as sources of TVOC. These high concentrations may result in irritation of the 459
upper airways and/or the lower respiratory tract and adverse lung effects (Rumchev et al., 460
2004; Nurmatov et al., 2013). 461
On weekends, no exceedances were observed. In general, most exceedances and non-462
compliances were registered in the urban nursery school. 463
3.4 Indoor/Outdoor ratios
464
The concentrations measured indoors were compared with those outdoors using the I/O 465
ratio for NO2 and O3. Median, minimum (min) and maximum (max) I/O ratios were
466
obtained for each studied room in the four nursery schools and are presented in Table 6. 467
Median I/O ratios of NO2 were lower than 1 in classroom A in full occupation and for
468
RUR1 lunch room in full occupation and partial occupation, meaning that lower 469
concentrations were observed indoors. In classrooms A during partial occupation and B, 470
both for weekdays and weekends, indoor air concentrations of NO2 were higher than
21 outdoors, which was probably due to accumulated indoor concentrations that did not 472
decrease as fast as the outdoor concentrations, leading to ratios higher than 1. Whichmann 473
et al. (2010) that studied indoor-outdoor relationships at homes, pre-schools and schools 474
in Stockholm (Sweden) also reported mean I/O ratio for pre-schools higher than 1. 475
I/O ratios found during the weekend were higher than those on weekdays, once again 476
demonstrating the contribution of accumulation observed in non-occupation periods 477
resulting from the lack of proper ventilation. 478
Maxima values of NO2 I/O ratios in URB were higher than in rural nursery schools. This
479
was expected since URB was strongly affected by traffic emissions and it is known that 480
NO2 is one of the main components of exhaust gases. Furthermore, the accumulation
481
phenomenon (lack of proper ventilation) increased even more the already high indoor 482
concentrations (influenced by outdoor air) in URB. 483
Concerning O3, I/O median ratios calculated for all microenvironments were lower than
484
1. This behaviour was expected, because in the absence of indoor sources, indoor O3
485
concentrations are mainly due to outdoor air. On average, I/O ratios were higher in rural 486
nursery schools than in the urban one. 487
488
4. Conclusions
489
Indoor concentrations of CO2, CO, CH2O, NO2, O3 and TVOC were monitored in rural
490
nursery schools and in one urban nursery school allowing a better understanding of the 491
effect that those two different contexts have on IAQ. 492
Regarding CO2, the urban nursery recorded, on average, higher concentrations than rural
493
nursery schools, reaching maxima peaks in occupation periods of around 7500 mg m-3. 494
22 The Portuguese legislation reference value was exceeded only in the classrooms from the 495
urban nursery, which was due to the higher occupation densities than in rural nursery 496
schools. CO and NO2 concentrations obtained in URB for occupation periods were on
497
average higher than those registered in rural nursery schools, which can be explained by 498
the influence of road traffic from outdoor air. The inexistence of indoor sources as well 499
as I/O ratio results indicated that the influence of outdoor air was the main determinant 500
NO2 and O3 indoor concentrations. Regarding O3, rural nursery schools registered higher
501
indoor concentrations than the urban nursery school. Several studies have concluded that 502
the outdoor O3 concentrations are clearly greater in rural areas than in urban ones (Sousa
503
et al., 2008). Thus, as no indoor sources were present (referred above) the higher rural 504
indoor concentration were due to the outdoor contribution. 505
High concentrations of CH2O and TVOC were occasionally observed associated mainly
506
to cleaning activities and in some cases indicating the presence of internal sources of these 507
pollutants, such as furniture finishing (emission of CH2O).
508
From this study it is possible to conclude that there is a need to implement measures to 509
reduce critical situations regarding IAQ and consequent children’s risk of exposure, 510
mainly in the urban context. Measures such as changing materials and consumer products 511
that emit VOC can be applied to promote children’s and childcare workers overall life 512
quality. More efficient ventilation (by mechanical or natural systems) could also be 513
applied to reach the same goal. Besides that, it could also be necessary to review the 514
Portuguese legislation on the number of children per classroom, having into account the 515
occupation density and children’s health issues. 516
The study allowed to communicate the results to the staff of the nursery schools involved 517
as well as to provide mitigation measures when necessary. The authors believe that these 518
23 findings may be useful to improve IAQ in other nursery schools and to support future 519
research. More nurseries need to be studied to help supporting these findings. 520
521
Acknowledgements
522
The authors are grateful to the nurseries involved in this study and to Comissão de 523
Coordenação e Desenvolvimento Regional do Norte (CCDR-N) for kindly providing the
524
outdoor air quality data. The authors are also grateful to Fundação para a Ciência e a 525
Tecnologia (FCT), COMPETE, QREN and EU for PTDC/SAU-SAP/121827/2010
526
funding. PTBS Branco and SIV Sousa are also grateful to FCT, POPH/QREN and 527
European Social Fund (ESF) for the financial support of grants SFRH/BD/97104/2013 528
and SFRD/BPD/91918/2012, respectively. 529
24
References
530
Annesi-Maesano, I., Baiz, N., Banerjee, S., Rudnai, P., Rive, S., & Group, S., 2013. 531
Indoor air quality and sources in schools and related health effects. J. Toxicol. Environ. 532
Health B. Crit. Rev., 16, 491-550. 533
Arbes, S. J., Sever, M., Mehta, J., Collete, N., Thomas, B., Zeldin, D. C., 2005. Exposure 534
to indoor allergens in day-care facilities: Results from 2 North Carolina counties. J. 535
Allergy. Clin. Immunol. 116, 133-139. 536
Ashmore, M. R., Dimitroulopoulu, C., 2009. Personal exposure of children to air 537
pollution. Atmos. Environ., 43, 128-141. 538
Ashrae., ASHRAE Standard 62.1-2007: ventilation for acceptable indoor air quality. The 539
American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), 540
Atlanta, GA. 2007. p. 46. 541
Bayer-Oglesby, L., Briggs, D., Hoek, G., Hoogh, K., Janssen, N., Jantunen, M., Sram, R., 542
Sanderson, E., Urbanus, J., 2004. Air-Pollution and risk to human health – exposure 543
assessment. Airnet work group 1. Available at
544
http://airnet.iras.uu.nl/products/pdf/airnetwg1exposurereport.pdf 545
Branco, P. T. B. S., Alvim-Ferraz, M. C. M., Martins, F. G., Sousa, S. I. V., 2014. The 546
microenvironmental modelling approach to assess children’s exposure to air pollution – 547
A review. Environ. Res. 135, 317-332. 548
Branco, P. T. B. S., Alvim-Ferraz, M. C. M., Martins, F. G., Sousa, S. I. V., 2015. 549
Children's exposure to indoor air in urban nurseries-part I: CO2 and comfort assessment.
550
Environ. Res. 140, 1-9. 551
25 Cano, M., Nogueira, S., Papoila, A. L., Aguiar, F., Martins, P., Marques, et al., Indoor 552
Air Quality in Portuguese Children Day Care Centres – ENVIRH Project. Proceedings of 553
the Second International Conference on Building Energy and Environment, pp. 414-421, 554
2012. 555
Carreiro-Martins, P., Viegas, J., Papoila, A. L., Aelenei, D., Caires, I., Araujo-Martins, J. 556
Gaspar-Marques J., Cano, M. M., Mendes, A. S., Virella, D., Rosado-Pinto, J., Leiria-557
Pinto, P., Annesi-Maesano, I., Neuparth, N., 2014. CO2 concentration in day care centres
558
is related to wheezing in attending children. Eur. J. Pediatr. 173, 1041-1049. 559
Csobod, É., Annesi-Maesano, I., Carrer, P., Kephalopoulos, S., Madureira, J., Rudnai, P., 560
Fernandes, E., Barrero-Moreno, J., Beregszászi, T., Hyvärinen, A., Moshammer, H., 561
Norback, D., Páldy, A., Pándics, T., Sestini, P., Stranger, M., Täubel, M., Varró, M. J., 562
Vaskovi, E., Ventura, G., Viegi, G., 2014. SINPHONIE (Schools Indoor Pollution and 563
Health Observatory Network in Europe): Executive Summary of the Final Report. Co-564
published by the European Commission’s Directorates General for Health and Consumers 565
and Joint Research Centre, Luxembourg. 566
Despacho n°5048-B/, Ministério da Educação e Ciência, Gabinetes do Secretário de 567
Estado do Ensino e da Administração Escolar e do Secretário de Estado do Ensino Básico 568
e Secundário, Diário da República-2ª Série, N°. 72 (5), 2013.12320(4)-12320. 569
de Gennaro, G., Dambruoso, P. D., Loiotile, A. D., Gilio, A. D., Giungato, P., Tutino, M., 570
Marzocca, A., Mazzone, A., Palmisani, J., Porcelli, F., 2014. Indoor air quality in schools. 571
Environ. Chem. Lett., 12, 467-482. 572
Duenas, C., Fernandez, M. C., Canete, S., Carretero, J., Liger, E., 2004. Analyses of ozone 573
in urban and rural sites in Malaga (Spain). Chemosphere 56, 631-639. 574
26 Faustman, E. M., Silbernagel, S. M., Fenske, R. A., Burbacher, T. M., Ponce R. A., 2000. 575
Mechanisms underlying children’s susceptibility to environmental toxicants. Environ. 576
Health. Perspect., 108, 13–21. 577
Franklin, P. J., 2007. Indoor air quality and respiratory health of children. Paediatr. 578
Respir. Rev., 8, 281–286. 579
Fromme, H., Lahrz, T., Kraft, M., Fembacher, L., Dietrich, S., Sievering, S., Burghardt, 580
R., Schuster, R., Bolte, G., Volkel, W., 2013. Phthalates in German daycare centers: 581
occurrence in air and dust and the excretion of their metabolites by children (LUPE 3). 582
Environ. Int., 61, 64-72. 583
Gładyszewska-Fiedoruk, K., 2011. Analysis of stack ventilation system effectiveness in 584
an average kindergarten in north-eastern Poland. Energy Build. 43, 2488 – 2493. 585
Griffiths, M., Eftekhari, M., 2008. Control of CO2 in a naturally ventilated classroom.
586
Energy and Build. 40, 556-560. 587
Jantunen, M., Asikaine, A., Hänninen, O., Hiltunen, L., Haverinen-Shaughnessy, U., 588
Arvela, H., McLaughlin, J., Vaskövi, É., 2008. EnVIE WP2 Final Report - Indoor Air 589
Pollution Exposure, KTL. 590
Jenkins, P. L., Phillips, T. J., Mulberg, E. J., & Hui, S. P., 1992. Activity patterns of 591
Californians: Use of and proximity to indoor pollutant sources. Atmos. Environ. Part A. 592
General Topics, 26, 2141-2148. 593
Jones, A.P., 1999. Indoor air quality and health. Atmos. Environ. 33, 4535–4564. 594
Klepeis, N. E., Nelson, W. C., Ott, W. R., Robinson, J. P., Tsang, A. M., Switzer, P., 595
Behar, J. V., Hern, S. C., Engelmann, W. H., 2001. The National Human Activity Pattern 596
27 Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J. Expo. 597
Anal. Environ. Epidemiol. 11, 231-252. 598
Kotzias, D., Geiss, O., Tirendi, S., Barrero-Moreno, J., Reina, V., Gotti, A., 2009. 599
Exposure to multiple air contaminants in public buildings, schools and kindergartens: the 600
European indoor air monitoring and exposure assessment (AIRMEX) study. Fresen. 601
Environ. Bull. 18, 670-681. 602
Missia, D. A., Demetriou, E., Michael, N., Tolis, E. I., and Bartzis, J. G., 2010. Indoor 603
exposure from building materials: A field study. Atmos. Environ. 44, 4388-4395. 604
Mohai, P., Kweon, B.S., Lee, S., Ard, K., 2011. Air pollution around schools is linked to 605
poorer student health and academic performance. Health Aff. 30, 852–862. 606
Nota Técnica NT-SCE02. 2009. Metodologia para auditorias periódicas de QAI em 607
edifícios de serviços existentes no âmbito do RSECE. 608
Nurmatov, U. B., Tagieva, N., Semple, S., Devereux, G., Sheikh, A., 2013. Volatile 609
organic compounds and risk of asthma and allergy: a systematic review and meta-analysis 610
of observational and interventional studies. Prim. Care Respir. J., 22, 9-15. 611
Nunes, R. A. O., Branco, P. T. B. S., Alvim-Ferraz, M. C. M., Martins, F. G., Sousa, S. 612
I. V., 2015. Particulate matter in rural and urban nursery schools in Portugal. Environ. 613
Pollut. 202, 7-16. 614
Portaria n° 262/, Ministério da Solidariedade e da Segurança Social – Diário da República 615
- 2ªSérie, N°.167, 2011. pp. 4338–4343. 616
28 Portaria n° 353-A/, Ministérios do Ambiente, Ordenamento do Território e Energia, da 617
Saúde e da Solidariedade, Emprego e Segurança Social – Diário da República - 1ªSérie, 618
N°.253 (9),2013. pp. 6644 (2)-6644. 619
Roda, C., Barral, S., Ravelomanantsoa, H., Dusséaux, M., Tribout, M., Le Moullec, Y., 620
Momas, I., 2011. Assessment f indoor environment in Paris child day care centres. 621
Environ. Res., 111, 1010-1017. 622
Rumchev, K., Spickett, J., Bulsara, M., Philips, M., Stick, S., 2004. Association of 623
domestic exposure to volatile organic compounds with asthma in young children. Thorax, 624
59, 746-751. 625
Schweizer, C., Edwards, R. D., Bayer-Oglesby, L., Gauderman, W. J., Ilacqua, V., 626
Jantunen, M. J., Lai, H. K., Nieuwenhuijsen, M., Kunzli, N., 2007. Indoor time-627
microenvironment-activity patterns in seven regions of Europe. J. Expo. Sci. Environ. 628
Epidemiol. 17, 170-181. 629
Silvers, A., Florence, B. T., Rourke, D. L., Lorimor, R. J., 1994. How children spend their 630
time: a sample survey for use in exposure and risk assessments. Risk. Anal. 14, 931-944. 631
Sofuoglu, S. C., Aslanb, G., Inal, F., Sofuoglu, A., 2011. An assessment of indoor air 632
concentrations and health risks of volatile organic compounds in three primary schools. 633
Int. J. Hyg. Environ. Health., 214, 36–46. 634
Sousa, S. I. V., Pereira, M. M. C., Martins, F. G., Alvim-Ferraz, C. M., 2008. 635
Identification of Regions with High Ozone Concentrations Aiming the Impact 636
Assessment on Childhood Asthma. Hum. Ecol. Risk Assess, 14:3, 610-622. 637
Sousa, S. I. V., 2009. Impact of Ozone on the Prevalence of Childhood Asthma. Ph.D., 638
thesis, Faculdade de Engenharia da Universidade do Porto, Porto. 639
29 Sousa, S. I. V., Ferraz, C., Alvim-Ferraz, M. C. M., Vaz, L. G., Marques, A. J., Martins 640
F. G., 2012. Indoor air pollution on nurseries and primary schools: impact on childhood 641
asthma- study protocol. BMC Public Health. 12, 435. 642
St-Jean, M., St-Amand, A., Gilbert, N. L., Soto, J. C., Guay, M., Davis, K., Gyorkos, T. 643
W., 2012. Indoor air quality in Montreal area day-care centres, Canada. Environ. Res. 644
118, 1-7. 645
Syri, S., Amann, M., Schopp, W., Heyes, C., 2001. Estimating long-term population 646
exposure to ozone in urban areas of Europe. Environ. Pollut. 113: 59-69. 647
Theodosiou, T. G., Ordoumpozanis, K. T., 2008. Energy, comfort and indoor air quality 648
in nursery and elementary school buildings in the cold climatic zone of Greece. Energy 649
and Buildings, 40, 2207-2214. 650
USEPA, 2009. Indoor Air Quality Tools for Schools - Reference Guide, U.S. 651
Environmental Protection Agency, Washington DC, USA. 652
Tiwary, A., Colls, J., 2010. Air pollutants - Sources and control of gases, in: T. F. Group 653
(Eds.), Air Pollution Measurement, modelling and mitigation Third edition. Oxon, pp. 3-654
5. 655
Venn, A. J., Cooper, M., Antoniak, M., Laughlin, C., Britton, J., Lewis, S. A., 2003. 656
Effects of volatile organic compounds, damp, and other environmental exposures in the 657
home on wheezing illness in children. Thorax, 58, 955-960. 658
Wang, J., Smedje, G., Nordquist, T., Norback, D., 2015. Personal and demographic 659
factors and change of subjective indoor air quality reported by school children in relation 660
to exposure at Swedish schools: a 2-year longitudinal study. Sci. Total. Environ. 508, 661
288-296. 662
30 WHO, 2006. Air Quality guidelines - Global update 2005, World Health Organization, 663
Regional Office for Europe, Copenhagen, Denmark. 664
WHO, 2010. WHO guidelines for indoor air quality: selected pollutants, World Health 665
Organisation, Regional office in Europe, European Series, Copenhagen, Denmark. 666
Wichmann, J., Lind, T., Nilsson, M.A.-M., Bellander, T., 2010. PM2.5, soot and NO2
667
indoor-outdoor relationships at homes, pre-schools and schools in Stockholm, Sweden. 668
Atmos. Environ. 44, 4536-4544. 669
Wu, C., Xu, B., Shi, S., Zhao, B., 2015. Time–activity pattern observatory from mobile 670
web logs. Int. J. of Embedded Systems. 7, 71-78. 671
Yang, W., Sohn, J., Kim, J., Son, B., Park, J., 2009. Indoor air quality investigation 672
according to age of the school buildings in Korea, J. of Environ. Manage. 90, 348-354. 673
Yoon, C., Lee, K., Park, D., 2011. Indoor air quality differences between urban and rural 674
preschools in Korea. Environ. Sci. Pollut. R. 18, 333-345. 675
Zhang, L. Z., and Niu, J. L., 2003. Effects of substrate parameters on the emissions of 676
volatile organic compounds from wet coating, Building Environment, 38, 939-946. 677
Zuraimi, M. S., and Tham, K. W., 2008. Indoor air quality and its determinants in tropical 678
child care centers, Atmos. Environ., 42, 2225-2239. 679
31
Figure captions
680
Figure 1. Daily profile of CO2 concentrations registered indoors for a) RUR1, b) RUR2,
681
c) RUR3, and d) URB. 682
Figure 2. Daily profile of CO concentrations registered indoors for a) RUR1, b) RUR2, 683
c) RUR3, and d) URB. 684
Figure 3. Daily profile of NO2 concentrations registered indoors for a) RUR1, b) RUR2,
685
c) RUR3, and d) URB. 686
Figure 4. Daily profile of O3 concentrations registered indoors in a) classroom A in FO
687
(week), classroom A in PO, classroom B (week and weekend) and lunch room in FO and 688
PO of RUR1, b) classroom A (week) and lunch room of RUR2, c) classroom A (week), 689
and d) URB. 690
Figure 5. Daily profile of TVOC concentrations registered indoors for a) RUR1, b) RUR2, 691
c) RUR3, and d) URB. 692
Figure 6. Daily profile of CH2O concentrations registered indoors in a) classroom A
693
(weekend), classroom B (weekdays) and lunch room in FO of RUR1, b) lunch room of 694
RUR2, c) lunch room of RUR3; and d) URB. 695
32
Table 1 – Summary of the main characteristics of each studied microenvironment and sampling periods.
Nursery Room Type of use Children’s
age (years) Floor
Area (m2) Occupation (Children + staff) Period of occupation Ventilation Sampling time (weekdays + weekend days) RUR1
A Classroom 4-5 Ground floor 63 FO
a : 25+2 POb : 6 + 2
09h – 12h 14h – 15h30
DNV c
(Door to inner corridor frequently closed; Windows frequently open; AVAC system
off)
2 + 2
B Classroom 5 Ground floor 48 20+2 09h – 12h
14h – 15h30
DNV
(Door to inner corridor frequently closed; Windows frequently open; AVAC system
off)
3 + 2
LR Lunch room 3-5 Ground floor
(back) 56
FO : ~200
PO : ~21 12h – 14h
DNV
(Open to kitchen and to inner corridor; Windows open during the occupation; AVAC
system off
1 + 0
RUR2
A Classroom 3-6 Ground floor
(back) 32.5 14+2
09h – 11h30 12h15 – 16h
DNV
(Door to inner corridor always open; Windows frequently closed; A/Cd and
heating off)
4 + 2
LR Lunch room 3-6 Ground floor 26 14+2 11h30 – 12h15
DNV
(Door to inner corridor always open; Windows open during the occupation)
3 + 0
RUR3
A Classroom <1-2 Ground floor 23.5 23+2
08h – 11h30 13h30 – 18h 12h30 – 15h30 (sleeping time)
DNV
(Door to inner corridor frequently closed; Windows frequently open; AVAC system
off)
4 + 2
B Classroom 2-3 Ground floor 37.5
1 (Functioned as support room) 8h – 11h30 12h30 – 18h DNV
(Door to inner corridor always closed; Windows always closed; AVAC system off)
3 + 0
LR Lunch room <1-3 Ground floor
(back) 104 24 11h30 – 12h30
DNV
(Door to inner corridor always open; Windows always closed; AVAC system off)
33
a FO – full occupation; b PO – partial occupation; c DNF – Dominate natural ventilation; d A/C – Air Conditioner; e DNF – Dominate forced ventilation.
Note: adapted from Nunes et al. (2005)
URB1 A Classroom <2 1st floor (back) 38 23+2 07h30 – 19h30 12h – 13h (sleeping time) DFV e
(Door to inner corridor always closed; A/C and dehumidifier frequently used)
4 + 2 B Classroom 2-3 1st floor (back) 21 23+2 08h30 – 10h50 11h45 – 18h30 12h – 15h (sleeping time) DFV
(Door to inner corridor always closed. Windows sometimes open; A/C and
dehumidifier frequently used)
4 + 0 C Classroom 4 2nd floor (front) 59 29+2 09h – 11h30 14h – 18h DNV
(Door to inner corridor always closed; Windows sometimes open)
3 + 2
LR Lunch room 2-5 Ground floor
(back) 38 21 to 74 11h30 – 13h30
DNV
(Opening to the kitchen and to the inner corridor; No direct opening to the outside)
34
Table 2 – Statistical parameters of the hourly mean data for each room studied at all nursery schools in weekdays for occupation periods.
Nursery RUR1 RUR2 RUR3 URB
Room AFOa APOb B c LRFO d LRPOe A LR f A g B LR A B C LR CO2 (mg m-3) Min 700 701 728 1092 885 953 1195 691 695 1622 823 715 773 1002 Max 2288 1490 1418 2431 1178 2398 1484 3490 1375 2513 3171 7448 4571 1331 Mean 1391 951 981 1808 1054 1565 1340 1883 1035 2068 2010 3791 2087 1202 Median 1397 828 932 1901 1068 1436 1340 1680 1021 2068 1940 4237 2126 1237 SD h 535 248 209 550 107 467 144 873 215 445 635 1938 971 122 CO (µg m-3) Min 3293.0 3496.6 1761.5 3172.2 2976.8 2772.5 1919.3 2667.2 2595.5 1535.7 2512.6 1646.7 1534.0 1591 Max 5972.0 4861.0 3206.3 3410.2 3515.8 3809.4 2259.8 3912.0 3109.9 1654.7 6686.5 6216.7 5386.6 1838 Mean 4417.7 4273.7 2583.9 3322.5 3309.6 3298.7 2089.5 3329.9 2872.0 1595.2 5031.7 3940.7 3692.4 1770 Median 3907.0 4319.6 2714.5 3385.2 3317.6 3285.6 2089.5 3344.2 2917.3 1595.2 5065.4 3609.8 4176.6 1824 SD 1030.0 441.8 431.9 106.8 175.5 261.5 170.3 325.6 141.1 59.5 1064.3 1167.6 1165.1 103 CH2O (µg m-3) Min 0.00 0.00 0.00 21.92 0.00 0.00 3.12 0.00 0.00 12.65 0.00 0.00 0.00 0.00 Max 0.00 0.00 61.79 233.76 0.00 0.00 72.95 0.00 0.00 42.94 653.44 697.74 0.00 12.21 Mean 0.00 0.00 5.62 112.80 0.00 0.00 38.03 0.00 0.00 27.79 99.32 72.94 0.00 4.50 Median 0.00 0.00 0.00 82.74 0.00 0.00 38.03 0.00 0.00 27.79 30.52 19.89 0.00 2.90 SD 0.00 0.00 17.76 89.06 0.00 0.00 34.91 0.00 0.00 15.14 162.55 126.91 0.00 5.04 NO2 (µg m-3) Min 0.00 5.99 56.14 0.00 9.20 38.26 0.00 72.79 82.84 2.22 98.58 0.64 15.15 6.32 Max 34.46 137.52 143.86 2.82 29.29 94.54 24.86 291.66 113.82 9.51 146.27 143.40 82.09 20.92 Mean 16.67 41.18 96.48 0.94 15.71 55.54 12.43 125.17 101.32 5.87 125.57 79.40 40.07 10.45 Median 17.07 24.26 94.11 0.00 13.42 50.67 12.43 117.77 101.65 5.87 127.74 89.26 35.52 7.27 SD 13.03 39.33 21.42 1.33 6.42 16.76 12.43 44.06 7.32 3.65 13.84 38.23 21.32 6.07 O3 (µg m-3) Min 2 0 6 0 1 0 0 0 0 0 0 0 0 2 Max 32 38 29 0 10 17 3 27 0 0 6 1 2 6 Mean 11 8 18 0 4 3 1 2 0 0 0 0 0 4 Median 8 4 16 0 3 1 1 0 0 0 0 0 0 4 SD 10 11 7 0 3 5 1 5 0 0 1 0 0 2
35 TVOC (µg m-3) Min 142.01 182.75 79.23 0.00 201.00 77.55 0.00 0.00 0.00 0.00 87.10 139.39 0.00 0.00 Max 174.17 325.63 488.33 0.00 450.12 140.20 0.00 1927.18 702.71 0.00 1245.68 1321.37 337.04 0.00 Mean 159.40 229.27 155.22 0.00 329.70 117.66 0.00 379.14 81.38 0.00 434.90 527.14 124.58 0.00 Median 160.44 219.66 100.47 0.00 357.65 118.04 0.00 0.00 0.00 0.00 295.23 527.21 118.05 0.00 SD 9.49 39.62 115.11 0.00 98.53 17.59 0.00 540.50 215.88 0.00 314.98 257.12 89.62 0.00 a A
FO – Classroom A in full occupation; b APO – Classroom A in partial occupation; c B – Classroom B; d LRFO – Lunch Room in full occupation; e LRPO – Lunch Room in partial occupation; f
